Imagine that two different data-mining teams of apparently comparable makeup and competence were given the same tools, access to the same data sets, and equal time to work. Later, the business managers who sponsored the projects looked back on their outcomes, and observed that one team's results were highly valued and influenced the business, whereas the other team's results were insignificant and soon forgotten. Imagine the managers now seeking to determine why two apparently identical projects could produce such different results. How would we help them? How would we study the problem? What performance variables would we measure? One way to address these questions is to consider how data mining can shape business decisions.